A Light Field Front-end for Robust SLAM in Dynamic Environments
Dynamic Channel Selection in UAVs through Constellations in the Sky
Multi-Sensor Mapping for Low Contrast, Quasi-Dynamic, Large Objects
Shah, V., Schild, K., Lindeman, M., Duncan, D., Sutherland, D., Cenedese, C., Straneo, F. and Singh, H., 2019. Multi-Sensor Mapping for Low Contrast, Quasi-Dynamic, Large Objects. IEEE Robotics and Automation Letters, 5(2), pp.470-476.
Iterative Labeling Process
Zhiyong Zhang, Samson Braun, Pushyami Kaveti
In this paper, we introduce a robust and cheap way to make training data set for object detection, especially for specialized fields that lack a large data set. The main idea of the Iterative Labeling Process is to train on predictions iteratively. Amazon MTurk is used to correct predictions. Auto-approval is applied to filter the MTurk results, which make the process fully automated. The process can save three times the common labeling cost. Furthermore, it can also complement missing objects and add ”background” labels in any existing data set. Train background labels can effectively reduce false positives.
Issues in the Design of Marine Vehicles: A Needs Based Analysis
Towards A COLREGs Compliant Autonomous Surface Vessel
Experimental Imaging Results of a UAV-mounted Downward-Looking mm-wave Radar
Zhang, W., Heredia-Juesas, J., Diddi, M., Tirado, L., Singh, H. and Martinez-Lorenzo, J.A., 2019, July. Experimental Imaging Results of a UAV-mounted Downward-Looking mm-wave Radar. In 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (pp. 1639-1640). IEEE.
Mobile Grasping & Tele-Operation
My research is focussed on developing and utilizing a mobile research platform with haptic feedback enabled tele-operation. We are currently in the process of developing and integrating the various systems; a Clearpath Husky mobile platform, a UR5e arm, and custom hydraulic grippers and controllers. Going forward we are interested in exploring mobile manipulation tasks, and using augmented perception schemes to improve the tele-operation experience. Later, we will work to mount a fully custom solution on an underwater robot, using haptic feedback to aide with manipulation tasks in low visibility environments.
Penguin Counting with Machine Learning
Strycker, N., Borowicz, A., Wethington, M., Forrest, S., Shah, V., Liu, Y., Singh, H. and Lynch, H.J., 2021. Fifty-year change in penguin abundance on Elephant Island, South Shetland Islands, Antarctica: results of the 2019–20 census. Polar Biology, 44(1), pp.45-56.
AirBeam: Experimental Demonstration of Distributed Beamforming by a Swarm of UAVs
Mohanti, S., Bocanegra, C., Meyer, J., Secinti, G., Diddi, M., Singh, H. and Chowdhury, K., 2019, November. AirBeam: Experimental Demonstration of Distributed Beamforming by a Swarm of UAVs. In 2019 IEEE 16th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) (pp. 162-170). IEEE.
AutOTranS: An Autonomous Open World Transportation System